{
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            "Development Status :: 5 - Production/Stable",
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            "Programming Language :: Python"
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        "description": "# liknorm-py\n\n[![Travis](https://img.shields.io/travis/com/limix/liknorm-py.svg?style=flat-square&label=linux%20%2F%20macos%20build)](https://travis-ci.com/limix/liknorm-py) [![AppVeyor](https://img.shields.io/appveyor/ci/Horta/liknorm-py.svg?style=flat-square&label=windows%20build)](https://ci.appveyor.com/project/Horta/liknorm-py)\n\nLiknorm Python wrapper.\n\n## Install\n\nIt can be done via [pip](https://pypi.org/) or [conda](https://conda.io/).\n\n### Pip\n\n```bash\npip install liknorm\n```\n\n### Conda\n\n```bash\nconda install -c conda-forge liknorm-py\n```\n\n## Running the tests\n\nAfter installation, you can test it\n\n```bash\npython -c \"import liknorm; liknorm.test()\"\n```\n\nas long as you have [pytest](http://docs.pytest.org/en/latest/).\n\n## Example\n\n```python\n>>> from numpy import empty\n>>> from numpy.random import RandomState\n>>> from liknorm import LikNormMachine\n>>>\n>>> machine = LikNormMachine('bernoulli')\n>>> random = RandomState(0)\n>>> outcome = random.randint(0, 2, 5)\n>>> tau = random.rand(5)\n>>> eta = random.randn(5) * tau\n>>>\n>>> log_zeroth = empty(5)\n>>> mean = empty(5)\n>>> variance = empty(5)\n>>>\n>>> moments = {'log_zeroth': log_zeroth, 'mean': mean, 'variance': variance}\n>>> machine.moments(outcome, eta, tau, moments)\n>>>\n>>> print('%.3f %.3f %.3f' % (log_zeroth[0], mean[0], variance[0]))\n-0.671 -0.515 0.946\n```\n\n## Authors\n\n* [Danilo Horta](https://github.com/horta)\n\n## License\n\nThis project is licensed under the [MIT License](https://raw.githubusercontent.com/limix/liknorm-py/master/LICENSE.md).\n\n\n",
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